No abstract

This paper investigates the antioxidant activity of fermented milk products obtained by kombucha fermentation. Two starter cultures were used as follows: starter obtained after kombucha fermentation on sweetened stinging nettle extract; as well as starter obtained after kombucha fermentation on sweetened winter savory extract. The starters were added to milk with 0.8, 1.6 and 2.8% milk fat. Fermentation was carried out at 37, 40 and 43oC and stopped when the pH reached 4.5. Antioxidant activity to hydroxyl and DPPH radicals was monitored using response surface methodology. Kombucha fermented milk products with stinging nettle (KSN) and with winter savory (KWS) showed the same antioxidant response to hydroxyl and different response to DPPH radicals. Synergetic effect of milk fat and fermentation temperature to antioxidant activity to hydroxyl radicals for both types of kombucha fermented milk products (KSN and KWS) was established. Optimum processing conditions in term of antioxidant activity are: milk fat around 2.8% and process temperature around 41 and 43°C for KSN and KWS respectively

No abstract

No abstract

No abstract

Wine industry generates large volumes of wastewaters resulting from numerous cleaning operations that occur during the different stages of winemaking. Disposal of these effluents in the environment causes huge problems due to their high organic and inorganic load and seasonal variability. The bioconversion of winery wastewaters in valuable product, such as xanthan, is an important alternative to overcome environmental problems. In this research, the possibility of xanthan production using Xanthomonas campestris on blended wastewaters from different stages of white and rose wine production with initial sugar content of 50 g/L was investigated. In addition to the media parameters (content of sugars, total and assimilable nitrogen, phosphorus, total dissolved salts and apparent viscosity), raw xanthan yield and degree of sugar conversion into product were determined in order to examine the success of xanthan biosynthesis. In applied experimental conditions, xanthan yield of 20.92 and 30.64 g/L and sugar conversion into product of 40.23 and 60.73% were achieved on wastewaters from white and rose wine production, respectively. The results of these experiments suggest that winery wastewaters, after additional optimization of the process in terms of the substrate composition and the cultivation conditions, may be a suitable raw material for industrial xanthan production.

Pepper bacterial spot is one of the most severe plant diseases in terms of infection persistence and economic losses when it comes to fresh pepper fruits used in nutrition and industrial processing. In this study, Bacillus velezensis IP22 isolated from fresh cheese was used as a biocontrol agent of pepper bacterial spot, whose main causal agent is the cosmopolitan pathogen Xanthomonas euvesicatoria. After optimization of the cultivation medium composition aimed at maximizing of the antimicrobial activity against X. euvesicatoria and validation of the optimized medium at the scale of a laboratory bioreactor, in planta tests were performed. The results have showed significant suppression of bacterial spot symptoms in pepper plants by the produced biocontrol agent, as well as reduction of disease spreading on the healthy (uninoculated) pepper leaves. Furthermore, HPLC-MS (high pressure liquid chromatography–mass spectrometry) analysis was employed to examine antimicrobial metabolites produced by B. velezensis IP22, where lipopeptides were found with similar m/z values compared to lipopeptides from fengycin and locillomycin families. The bioprocess solution developed at the laboratory scale investigated in this study represents a promising strategy for production of pepper bacterial spot biocontrol agent based on B. velezensis IP22, a food isolate with a great perspective for application in plant protection.

a b s t r a c tThe aim of this work was to model and predict the process of bioethanol production from intermediates and byproduct of sugar beet processing by applying artificial neural networks. Prediction of one substrate fermentation by neural networks had the same input variables (fermentation time and starting sugar content) and one output value (ethanol content, yeast cell number or sugar content). Results showed that a good prediction model could be obtained by networks with single hidden layer. The neural network configuration that gave the best prediction for raw or thin juice fermentation was one with 8 neurons in hidden layer for all observed outputs. On the other side, the optimal number of neurons in hidden layer was found to be 9 and 10 for thick juice and molasses, respectively. Further, all substrates data were merged, which led to introducing an additional input (substrate type) and defining all outputs optimal network architecture to 3-12-1. From the results the conclusion was that artificial neural networks are a good prediction tool for the selected network outputs. Also, these predictive capabilities allowed the application of the Garson's equation for estimating the contribution of selected process parameters on the defined outputs with satisfactory accuracy.